A benefit of a flexible manipulator is that it can be placed into constrained environments, where its body can conform around and interact with obstacles in a safe manner. Because of this, flexible manipulators have a fast-growing number of applications, including in medicine, where the flexibility of a manipulator allows for safe, minimally invasive interventions. However, because the flexibility of the manipulator body may allow for infinite degrees of freedom, it is a challenging task to accurately model and then control the positioning of the manipulator, especially in the presence of constraints. Accordingly, problems with models arise when a flexible manipulator is introduced into an environment with unknown constraints.